1. Field of the Invention
The present invention is in the field of information recognition.
2. Description of the Related Art
The need to perform automated speech recognition for large, practically open-ended compendiums of automated speech is arising more frequently in state-of-the art applications of automated speech match.
The invention described in the following text may address two issues:                a) If an automated speech recognition directory's internal architecture is based on a given structure, there is a positive likelihood that consecutive entries share a certain degree of similarity. This can be observed, for example, in directories with an alphabetic dictionary-like structure or in cases where consecutive entries represent variations or permutations of one entry of higher order. When an automated speech recognition program scans such a directory in order to find a match for an audio input the occurrence of artifacts based on this proximity of similar entries is likely, which may compromise recognition quality. Therefore there exists a need for a method that ensures that the entries in an automated speech recognition directory are as dissimilar as possible.        b) Automated speech recognition software is usually optimized for directory files of a certain maximum size. Larger sizes not only slow down processing speed but also compromise the recognition quality. Since directory sizes in industrial applications often surpass this maximum size, there exists a need for a method that allows the software to adapt to those larger directories, either for automated speech recognition application, or other intelligent matching and recognition processes such as for example, automated speech recognition and automated speech matching based applications. For brevity in the following automated speech recognition refers to the fully spectrum of such applications.        